Examine neural networks in Python. The dataset has 20 records and 19 different attributes about smartphone specifications. The goal in this analysis is to predict the price of a smartphone based on its attributes using neural network techniques. This data set has the following price range: 0 for low, 1 for middle, 2 for expensive, and 3 for very expensive. Preparing the data for a neural network is very important. The data needs to be divided into training (70%) and testing (30%) datasets.

battery_power	bluetooth	clock_speed	dual_sim	frontcamerapixel	4G	memorysize	weight	cores	primarycamerapixel	pixelresolutionheight	pixelresolutionwidth	ram	screenheight	screenwidth	talk_time	3G	touch_screen	wifi	price_range
842	0	2.2	0	1	0	7	188	2	2	20	756	2549	9	7	19	0	0	1	1
1021	1	0.5	1	0	1	53	136	3	6	905	1988	2631	17	3	7	1	1	0	2
563	1	0.5	1	2	1	41	145	5	6	1263	1716	2603	11	2	9	1	1	0	2